Data Scientist

We are seeking an analytical and detail-oriented Data Scientist to transform complex data into actionable business insights. In this role, you will design statistical models, build predictive machine learning algorithms, and analyze large datasets to solve key business problems. You will work closely with cross-functional teams, including engineering, product management, and business analytics.

Key Responsibilities

• Model Development: Design, build, and deploy machine learning algorithms and predictive models (e.g., classification, regression, clustering, NLP, or time-series analysis).
• Data Mining & Extraction: Extract, clean, and preprocess large structure and unstructured datasets from diverse databases and cloud sources.
• Exploratory Data Analysis (EDA): Perform in-depth quantitative analysis to identify trends, patterns, and anomalies in complex datasets.
• A/B Testing & Experimentation: Design, execute, and evaluate experimental setups and hypothesis tests to guide product and operational decisions.
• Data Visualization & Reporting: Build interactive dashboards and reporting tools (e.g., Tableau, Power BI, or Looker) to communicate technical findings to stakeholders.
• Cross-Functional Collaboration: Partner with data engineers to streamline data pipelines and support model deployment into production environments.

Required Qualifications & Skills

• Experience: 3+ years of professional experience in a Data Scientist or quantitative analytics role.
• Programming Skills: Advanced proficiency in Python or R, along with libraries like Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch.
• SQL Proficiency: Expert knowledge of complex SQL querying, schema design, and database management.
• Mathematics & Statistics: Strong foundation in probability, statistics, linear algebra, and experimental design.
• Communication: Ability to translate complex algorithmic concepts into actionable insights for non-technical stakeholders.

Preferred Qualifications

• Master’s degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Databricks).
• Familiarity with containerization tools (Docker, Kubernetes) and MLOps practices.

Benefits

• Health, Dental, and Vision Insurance
• Paid Time Off (PTO) & Paid Holidays
• 401(k) / Retirement plan with company match
• Flexible working arrangements (Remote/Hybrid options)
• Annual learning allowance for certifications and conferences